With the development and the use of a large variety.of. DB schemas and ontologies, in many domains (e.g. semantic web, digital libraries, life science, etc), matching techniques are called to overcome the challenge of aligning and reconciling these different interrelated representations. Matching field is becoming a very attractive research topic. In this paper, we are interested in studying scalable matching problem. We survey the approaches and tools of large scale matching, when a large number of schemas/ontologies and attributes are involved. We attempt to cover a variety of techniques for schema matching called Pair-wise and Holistic. One can acknowledge that this domain is on top of effervescence and scalable matching needs many more advances. Therefore, we propose our scalable schema matching methodology that deals with the creation of a hybrid approach combining these techniques. Our architecture includes a pre-matching approach based on XML schemas decomposition. As shown by our experiments, our proposed methodology has been evaluated and implementing in a PLASMA (Platform for Large Scale schema MAtching) prototype.